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» Improved Segmentation Based on Probabilistic Labeling
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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 8 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
CVPR
2012
IEEE
11 years 11 months ago
Weakly supervised structured output learning for semantic segmentation
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
ISMIR
2004
Springer
236views Music» more  ISMIR 2004»
14 years 1 months ago
Rhythm and Tempo Recognition of Music Performance from a Probabilistic Approach
This paper concerns both rhythm recognition and tempo analysis of expressive music performance based on a probabilistic approach. In rhythm recognition, the modern continuous spee...
Haruto Takeda, Takuya Nishimoto, Shigeki Sagayama
MICCAI
2008
Springer
14 years 9 months ago
A Discriminative Model-Constrained Graph Cuts Approach to Fully Automated Pediatric Brain Tumor Segmentation in 3-D MRI
In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation app...
Michael Wels, Gustavo Carneiro, Alexander Aplas,...
IROS
2006
IEEE
132views Robotics» more  IROS 2006»
14 years 2 months ago
Supervised Learning of Topological Maps using Semantic Information Extracted from Range Data
Abstract— This paper presents an approach to create topological maps from geometric maps obtained with a mobile robot in an indoor-environment using range data. Our approach util...
Óscar Martínez Mozos, Wolfram Burgar...